This application relates generally to biometrics. More specifically, this applications relates to methods and systems for detecting attempts to spoof biometric systems.
“Biometrics” refers generally to the statistical analysis of characteristics of living bodies. One category of biometrics includes “biometric identification,” which commonly operates under one of two modes to provide automatic identification of people or to verify purported identities of people. Biometric sensing technologies measure he physical features or behavioral characteristics of a person and compare those features to similar prerecorded measurements to determine whether there is a match. Physical features that are commonly used for biometric identification include faces, irises, hand geometry, vein structure, and fingerprint patterns, which is the most prevalent of all biometric-identification features. Current methods for analyzing collected fingerprints include optical, capacitive, radio-frequency, thermal, ultrasonic, and several other less common techniques.
Most of the fingerprint-collection methods rely on measuring characteristics of the skin at or very near the surface of a finger. In particular, optical fingerprint readers typically rely on the presence or absence of a difference in the index of refraction between the sensor platen and the finger placed on it. When the angle of light at an interface is greater than the critical angle and an air-filled valley of the fingerprint is present at a particular location of the platen, total internal reflectance (“TIR”) occurs in the platen because of the air-platen index difference. Alternatively, if skin of the proper index of refraction is in optical contact with the platen, the TIR at this location is “frustrated,” allowing light to traverse the platen-skin interface. A map of the differences in TIR across the region where the finger is touching the platen forms the basis for a conventional optical fingerprint reading. There are a number of optical arrangements used to detect this variation of the optical interface in both bright-field and dark-field optical arrangements. Commonly, a single quasimonochromatic beam of light is used to perform this TIR-based measurement.
There also exists non-TIR optical fingerprint sensors. Some non-TIR contact sensors rely on some arrangement of quasimonochromatic light to illuminate the front, sides, or back of a fingertip, causing the light to diffuse through the skin. The fingerprint image is formed because of the differences in light transmission through the finger and across the skin-platen interface for the ridge and valleys. The difference in optical transmission at the interface is due to changes in the Fresnel reflection characteristics that result from the presence or absence of intermediate air gaps in the valleys. Some non-TIR sensors are non-contact sensors, which use polarized light to image the surface features of the finger. In some cases the imaging system may include a linear polarizer and the illumination light may be polarized in parallel and perpendicular directions to provide two images, which are then combined in some manner to enhance the surface features of the finger.
Although optical fingerprint readers based on TIR phenomena are one of the most commonly deployed types of fingerprint sensors, they are susceptible to image-quality problems due to non-ideal conditions. If the skin is overly dry, the index match with the platen will be compromised, resulting in poor image contrast. Similarly, if the finger is very wet, the valleys may fill with water, causing an optical coupling to occur all across the fingerprint region and greatly reduce image contrast. Similar effects may occur if the pressure of the finger on the platen is too little or too great, the skin or sensor is dirty, the skin is aged and/or worn, or overly fine features are present such as may be the case for certain ethnic groups and in very young children. These effects decrease image quality and thereby decrease the overall performance of the fingerprint sensor. In one recent study, 16% of fingerprint images were found to be of suboptimal image quality as a result of these effects. In some cases, commercial optical fingerprint readers incorporate a thin membrane of soft material such as silicone to help mitigate some of these effects and restore performance. As a soft material, the membrane is subject to damage, wear, and contamination, limiting the use of the sensor before it requires maintenance.
Biometric sensors, particularly fingerprint biometric sensors, are generally prone to being defeated by various forms of spoof samples. In the case of fingerprint readers, a variety of methods are known in the art for presenting readers with a fingerprint pattern of an authorized user that is embedded in some kind of inanimate material such as paper, gelatin, epoxy, latex, or the like. Thus, even if a fingerprint reader can be considered to reliably determine the presence or absence of a matching fingerprint pattern, it is also critical to the overall system security to ensure that the matching pattern is being acquired from a genuine, living finger, which is difficult to ascertain with many existing sensors.
There is accordingly a general need in the art for improved biometric sensing techniques resistant to spoofing.